An Efficient Automatic Gait Anomaly Detection Method Based on Semisupervised Clustering

Table 6

The CPU timing of the test case II by the AGD-SSC, AGD-SSC-NBC, IF, and LOF.

Seq no.	AGD-SSC; mean (st. dev.)	AGD-SSC-NBC; mean (st. dev.)	IF mean (st. dev.)	LOF mean (st. dev.)
Seq. 1	1.8829 (0.0198)	2.1767 (0.0168)	10.7176 (0.0397)	0.9176 (0.0064)
Seq. 2	1.6232 (0.0606)	2.8794 (0.0934)	10.7297 (0.0596)	0.9319 (0.0280)
Seq. 3	1.2637 (0.0333)	2.3155 (0.0365)	10.7345 (0.0681)	0.9293 (0.0224)
Seq. 4	1.7210 (0.0357)	2.2155 (0.0327)	10.7328 (0.0721)	0.9261 (0.0203)
Seq. 5	1.1815 (0.0096)	2.1598 (0.0625)	10.7578 (0.2188)	0.9231 (0.0108)
Seq. 6	1.1071 (0.0366)	2.2243 (0.0303)	10.7458 (0.0954)	0.9265 (0.0231)
Seq. 7	1.3799 (0.0291)	2.0953 (0.0304)	10.7269 (0.0342)	0.9274 (0.0214)
Seq. 8	1.2086 (0.0247)	2.0500 (0.0354)	10.7376 (0.0957)	0.9272 (0.0229)
Seq. 9	1.3493 (0.0152)	2.1763 (0.0381)	10.7269 (0.0455)	0.9248 (0.0062)
Seq. 10	1.2157 (0.0347)	2.1177 (0.0327)	10.7687 (0.1951)	0.9276 (0.0251)
Average	1.3933	2.2411	10.7378	0.9262